On Wednesday, 6 January 2016 at 05:43:37 UTC, Jason Jeffory wrote:
Yeah, I'm not sure I understand the StackOverflow thing but it would be cool if people didn't waste so much time having to do the same boilerplate code.
What I meant is that often what we seek is recipes for solving specific problems. Python is pretty high level and expressive. Quite often we find cut'n'paste solutions in Python to specific problems.
What if we had a better way of locating recipes? What if we had high level recipes and an AI program that could turn it into something more specific and executable?
Basically we not only need a better programming language, but a language for helping the AI to locate the best recipes and a global infrastructure that can provide all this knowledge compilers.
I'm not sure if AI is far enough along. Proper AI learning algorithms could potentially help(they might suck at first but this is what training/practice is for. Eventually they will be better at it than us
I think we need more computational power. Which will happen, but takes time. In our computers the physical chip is the size of a confetti. One idea that is being explored is to build chips as "cubes" with pipes through them for efficient cooling. And we need lots of storage too. Chess players memorize good moves given specific configurations, compilers should too. Our compilers don't learn... that's rather primitive.
There are solutions that generate machine language by stringing together random sequences of instructions and selecting the ones that can become part of a working program. But it takes lots of computing. With more computing power and storage it might become practical, but we'll see more efficient AI based approaches. Still, stochastic optimizers like STOKE is hinting of what might come.
https://cs.stanford.edu/people/eschkufz/ https://github.com/StanfordPL/stoke-release
all out... we are on track. It just feels like there it is very inefficient... but like most things, it tends to be exponential.
Yes, or maybe we need _lots_ of storage. It seems to help chess computers. Storage also don't need as much energy as computation, so it is easier to scale up? Just think about how much storage one cubic meter of memorysticks represents... and we are only at the beginning of solid state storage.
Our brain is also quite slow, I think parts of it is working at 100hz? But we have lots of relevant information in storage to access ("experience").
I suppose the average programmer can't comprehend the complexities require for the initial adaptation and it takes time for them to "get with the program". Think of when C added ++... most programmers were not good at oop... now it seems everyone has a pretty solid understanding of it.
Yes, tradition can be limiting. Most have a fair understanding of OOP, but many also don't understand that OO is more about modelling than programming and can be implemented in any language... So I think you are right, programmers probably think in rather concrete terms of their code, but the kind of futuristic programming language need more abstract thinking than commercial languages require.
I remember a visit with a game company in the 90s. They said that many of their original coders left when they transitioned from coding in assembler to C/C++, the programmers had trouble changing how they thought about programming to a higher level.
For us that is difficult to understand, right?
